The intention of the workshop is to bring together
researchers from the two research areas Semantic Web and
Knowledge Discovery. According to T. Berners-Lee the
Semantic Web is "an extension of the current web in which
information is given well-defined meaning, better enabling
computers and people to work in cooperation". Current
standardization efforts include e.g. the W3C recommendation for
the Web Ontology Language (OWL). Knowledge Discovery is defined by
U.M. Fayyad as "the nontrivial process of identifying valid,
previously unknown, potentially useful patterns in data".

We foresee two ways of combining these areas. On the one hand,
mining for the semantic web includes the application of
knowledge discovery methods and techniques to support the setting
up of the semantic web itself. Prominent examples are here
ontology learning and population of ontologies (instance
learning). On the other hand, mining from the semantic
web emphasizes the usage of semantic web technologies for mining
purposes such as e.g. the usage of taxonomies in recommender
systems, applying association rules with generalizations or
clustering with background knowledge in form of ontologies.

Although not required for the initial submission, we recommend to follow the format
guidelines of KDD (Springer LNCS), as this will be the required format for accepted papers
(cf. instructions).

Note: Please also check the list of topics in the KDD
Workshop on Web Mining and Web Usage Analysis (WebKDD).
You should consider submitting your paper to WebKDD, if the primary topics covered by the paper relate more directly to usage mining or recommendation and personalisation techniques.
Given certain amount of overlap between the topics covered by the two workshops, some of the papers submitted to each workshop will be selected for presentation at a joint session.
More details about the joint session will be posted at a later date.